Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

Estimating State-contingent Production Frontiers

Chambers and Quiggin (2000) use state-contingent representations of risky production technologies to establish important theoretical results concerning producer behavior under uncertainty. Unfortunately, perceived problems in the estimation of state-contingent models have limited the usefulness of the approach in policy formulation. We show that fixed and random effects state-contingent production frontiers can be conveniently estimated in a finite mixtures framework. An empirical example is provided. Compared to conventional estimation approaches, we find that estimating production frontiers in a statecontingent framework produces significantly different estimates of elasticities, firm technical efficiencies and other quantities of economic interest.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

A learning approach for performance evaluation of local network

In this paper, a novel approach is developed to evaluate the overall performance of a local area network as well as to monitor some possible intrusion detections. The data is obtained via system utility 'ping' and huge data is analyzed via statistical methods. Finally, an overall performance index is defined and simulation experiments in three months proved the effectiveness of the proposed performance index. A software package is developed based on these ideas.

ANÁLISE DA INTERDEPENDÊNCIA DO CAPITAL PSICOLÓGICO, PERCEPÇÕES DE SUPORTE E BEM-ESTAR NO TRABALHO

Em face da complexidade no ambiente de trabalho que exige maior dedicação por parte de seus ocupantes e com uma crescente exigência por desempenho destes indivíduos, o presente estudo teve por objetivo estudar a interdependência de algumas variáveis do comportamento organizacional, testando um modelo conceitual composto do capital psicológico, percepções de suporte e bem-estar no trabalho. Os participantes foram 152 trabalhadores que atuavam na Região Norte (Estado do Tocantins) e Região Sudeste (Estado de São Paulo) em organizações públicas e privadas. Como instrumento para coleta de dados foi utilizado um questionário de autopreenchimento composto de seis escalas que mediram as variáveis da pesquisa. A presente pesquisa se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar as hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa de natureza transversal com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculos de estatísticas descritivas: médias, desvio padrão, teste t e correlações; cálculos de estatísticas multivariadas: análises de regressões lineares múltiplas hierárquicas e stepwise) por meio do software SPSS, versão 18.0. Os resultados obtidos demonstraram que os níveis das três dimensões de bem-estar no trabalho são impactados diretamente pelas percepções de suporte (social no trabalho e organizacional). Confirmou-se também, o capital psicológico como preditor direto das percepções de suporte (social no trabalho e organizacional). Por fim, este trabalho evidenciou que trabalhadores com um capital psicológico elevado tendem a perceber suporte, tanto social no trabalho como organizacional e, por conseguinte, trabalhadores que percebem suporte (social no trabalho e organizacional) tendem a manter vínculos com seu trabalho e com sua organização empregadora, os quais representam bem-estar no trabalho.

O PAPEL MODERADOR DE ESTILOS DE LIDERANÇA NA RELAÇÃO ENTRE PERCEPÇÃO DE SUPORTE ORGANIZACIONAL E COMPROMETIMENTO ORGANIZACIONAL AFETIVO: UM ESTUDO COM TRABALHADORES DA REGIÃO SUDESTE DO BRASIL

Esta dissertação teve como objetivo geral analisar as relações entre estilos de liderança, percepção de suporte organizacional e comprometimento organizacional afetivo em trabalhadores. Participaram da pesquisa 263 trabalhadores que atuam na Região Sudeste do Brasil (Rio de Janeiro e São Paulo) em organizações não governamentais, públicas e privadas. Como instrumento para coleta de dados foi utilizado um questionário de autopreenchimento composto de três escalas que mediram as variáveis da pesquisa. O estudo se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar as hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa de natureza transversal com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculos de estatísticas descritivas: médias, desvio padrão, teste t e correlações; cálculos de estatísticas multivariadas: análises de regressões lineares múltiplas hierárquicas). O tratamento e análise dos dados foram realizados pelo software estatístico Statistical Package for the Social Science SPSS, versão 18.0 para Windows. Os resultados obtidos demonstraram que a variável percepção de suporte organizacional exerce forte e significativo impacto sobre comprometimento organizacional afetivo, enquanto que a variável estilos de liderança não consegue aumentar nem diminuir a força. A pesquisa possibilitou concluir pela adequação parcial do modelo testado visto ser a variável estilos de liderança um moderador frágil da relação entre percepção de suporte organizacional e comprometimento organizacional afetivo.

O IMPACTO DE PERCEPÇÃO DE SUPORTE ORGANIZACIONAL E COMPROMETIMENTO ORGANIZACIONAL AFETIVO SOBRE A INTENÇÃO DE ROTATIVIDADE

O objetivo geral deste estudo foi analisar, interpretar e discutir as relações entre a percepção de suporte organizacional, comprometimento organizacional afetivo e intenção de rotatividade e os efeitos das variáveis: gênero, idade, tempo de trabalho e chefia sobre a intenção de rotatividade. Participaram deste estudo 132 trabalhadores que atuam no estado de São Paulo em organizações públicas e privadas. Como instrumento para a coleta de dados foi utilizado um questionário de autopreenchimento composto por três escalas que mediram as variáveis. A presente pesquisa se propôs a apresentar, interpretar e discutir as relações entre as variáveis, como também, testar as hipóteses referentes ao modelo conceitual proposto, por meio de uma pesquisa de natureza transversal com abordagem quantitativa, cujos dados coletados foram analisados por aplicação de técnicas estatísticas paramétricas (cálculos de estatísticas descritivas: médias, desvio padrão, teste t student, correlações e cálculos de estatísticas multivariadas: analise da regressão múltipla hierárquica). O tratamento e análise dos dados foram realizados pelo software estatístico Statistical Package for Social Science SPSS, versão 19.0 para Windows. Os resultados obtidos demonstraram que percepção de suporte organizacional e o comprometimento organizacional são preditores diretos de intenção de rotatividade. As variáveis: gênero, idade, tempo de trabalho e chefia não apresentaram coeficientes de regressão significantes, portanto não é possível afirmar que são antecedentes de intenção de rotatividade. Os resultados foram discutidos à luz da literatura da área, tendo sido comparados com resultados de outros estudos empíricos.

Leading edge forecasting techniques for exchange rate prediction

This paper describes how modern machine learning techniques can be used in conjunction with statistical methods to forecast short term movements in exchange rates, producing models suitable for use in trading. It compares the results achieved by two different techniques, and shows how they can be used in a complementary fashion. The paper draws on experience of both inter- and intra-day forecasting taken from earlier studies conducted by Logica and Chemical Bank Quantitative Research and Trading (QRT) group's experience in developing trading models.

What does the study of the spatial patterns of pathological lesions tell us about the pathogenesis of neurodegenerative disorders?

Discrete pathological lesions, which include extracellular protein deposits, intracellular inclusions and changes in cell morphology, occur in the brain in the majority of neurodegenerative disorders. These lesions are not randomly distributed in the brain but exhibit a spatial pattern, that is, a departure from randomness towards regularity or clustering. The spatial pattern of a lesion may reflect pathological processes affecting particular neuroanatomical structures and, therefore, studies of spatial pattern may help to elucidate the pathogenesis of a lesion and of the disorders themselves. The present article reviews first, the statistical methods used to detect spatial patterns and second, the types of spatial patterns exhibited by pathological lesions in a variety of disorders which include Alzheimer's disease, Down syndrome, dementia with Lewy bodies, Creutzfeldt-Jakob disease, Pick's disease and corticobasal degeneration. These studies suggest that despite the morphological and molecular diversity of brain lesions, they often exhibit a common type of spatial pattern (i.e. aggregation into clusters that are regularly distributed in the tissue). The pathogenic implications of spatial pattern analysis are discussed with reference to the individual disorders and to studies of neurodegeneration as a whole.

Strategic group theory:review, examination and application in the UK pharmaceutical industry

Purpose – The purpose of this paper is to consider the current status of strategic group theory in the light of developments over the last three decades. and then to discuss the continuing value of the concept, both to strategic management research and practising managers. Design/methodology/approach – Critical review of the idea of strategic groups together with a practical strategic mapping illustration. Findings – Strategic group theory still provides a useful approach for management research, which allows a detailed appraisal and comparison of company strategies within an industry. Research limitations/ implications – Strategic group research would undoubtedly benefit from more directly comparable, industry-specific studies, with a more careful focus on variable selection and the statistical methods used for validation. Future studies should aim to build sets of industry specific variables that describe strategic choice within that industry. The statistical methods used to identify strategic groupings need to be robust to ensure that strategic groups are not solely an artefact of method. Practical implications – The paper looks specifically at an application of strategic group theory in the UK pharmaceutical industry. The practical benefits of strategic groups as a classification system and of strategic mapping as a strategy development and analysis tool are discussed. Originality/value – The review of strategic group theory alongside alternative taxonomies and application of the concept to the UK pharmaceutical industry.

Statnote 29:discriminant analysis

Discriminant analysis (also known as discriminant function analysis or multiple discriminant analysis) is a multivariate statistical method of testing the degree to which two or more populations may overlap with each other. It was devised independently by several statisticians including Fisher, Mahalanobis, and Hotelling ). The technique has several possible applications in Microbiology. First, in a clinical microbiological setting, if two different infectious diseases were defined by a number of clinical and pathological variables, it may be useful to decide which measurements were the most effective at distinguishing between the two diseases. Second, in an environmental microbiological setting, the technique could be used to study the relationships between different populations, e.g., to what extent do the properties of soils in which the bacterium Azotobacter is found differ from those in which it is absent? Third, the method can be used as a multivariate ‘t’ test , i.e., given a number of related measurements on two groups, the analysis can provide a single test of the hypothesis that the two populations have the same means for all the variables studied. This statnote describes one of the most popular applications of discriminant analysis in identifying the descriptive variables that can distinguish between two populations.

Measuring the degree of spatial correlation between histological features in thin sections of brain tissue

Histological features visible in thin sections of brain tissue, such as neuronal perikarya, blood vessels, or pathological lesions may exhibit a degree of spatial association or correlation. In neurodegenerative disorders such as AD, Pick's disease, and CJD, information on whether different types of pathological lesion are spatially correlated may be useful in elucidating disease pathogenesis. In the present article the statistical methods available for studying spatial association in histological sections are reviewed. These include tests of interspecific association between two or more histological features using χ2 contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, the use of correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.